A Novel Parameter Initialization Technique Using RBM-NN for Human Action Recognition
Joint Authors
Roselind Johnson, Deepika
Uthariaraj, V.Rhymend
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-30, 30 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-10
Country of Publication
Egypt
No. of Pages
30
Main Subjects
Abstract EN
Human action recognition is a trending topic in the field of computer vision and its allied fields.
The goal of human action recognition is to identify any human action that takes place in an image or a video dataset.
For instance, the actions include walking, running, jumping, throwing, and much more.
Existing human action recognition techniques have their own set of limitations when it concerns model accuracy and flexibility.
To overcome these limitations, deep learning technologies were implemented.
In the deep learning approach, a model learns by itself to improve its recognition accuracy and avoids problems such as gradient eruption, overfitting, and underfitting.
In this paper, we propose a novel parameter initialization technique using the Maxout activation function.
Firstly, human action is detected and tracked from the video dataset to learn the spatial-temporal features.
Secondly, the extracted feature descriptors are trained using the RBM-NN.
Thirdly, the local features are encoded into global features using an integrated forward and backward propagation process via RBM-NN.
Finally, an SVM classifier recognizes the human actions in the video dataset.
The experimental analysis performed on various benchmark datasets showed an improved recognition rate when compared to other state-of-the-art learning models.
American Psychological Association (APA)
Roselind Johnson, Deepika& Uthariaraj, V.Rhymend. 2020. A Novel Parameter Initialization Technique Using RBM-NN for Human Action Recognition. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-30.
https://search.emarefa.net/detail/BIM-1138901
Modern Language Association (MLA)
Roselind Johnson, Deepika& Uthariaraj, V.Rhymend. A Novel Parameter Initialization Technique Using RBM-NN for Human Action Recognition. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-30.
https://search.emarefa.net/detail/BIM-1138901
American Medical Association (AMA)
Roselind Johnson, Deepika& Uthariaraj, V.Rhymend. A Novel Parameter Initialization Technique Using RBM-NN for Human Action Recognition. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-30.
https://search.emarefa.net/detail/BIM-1138901
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138901